7 results about "Local planning" patented technology

This invention discloses a collaborative path planning method based on multi-constraint improved A* algorithm and a dynamic look-ahead mechanism. It constructs a feature distance field map containing a nonlinear safety potential field, transforming discrete environmental information into continuous safety gradients. An improved A* algorithm, incorporating dynamic adaptive heuristic weights, nonlinear safety potential field costs, and kinematic smoothness constraints, is used to plan the globally optimal path. A velocity-adaptive dynamic look-ahead mechanism is established to calculate dynamic look-ahead points that conform to the current motion state in real time. A multi-objective evaluation function containing a global traction index is introduced into the local planning process to optimize control commands by measuring the deviation between the local trajectory and the global intent. This invention effectively solves the problems of "wall-hugging effect," high computational cost in large-scale environments, and poor coordination between global and local planning in traditional methods, improving the navigation safety and smoothness of robots in complex unstructured scenarios.

This invention relates to a multi-task path planning method for a self-balancing bicycle robot, belonging to the field of autonomous navigation technology for mobile robots. The method includes: constructing an environmental grid model containing static obstacle information; fusing obstacle repulsion forces and a Venn diagram skeleton to guide the generation of a safe environmental potential field; receiving a sequence of multi-task target points and calculating the optimal heading angle for each target point; performing a global path search in a three-dimensional state space using forward-backward dual-modal primitives to generate a global path that satisfies nonholonomic kinematic constraints; and employing an improved dynamic window algorithm for local planning, performing dynamic stability verification and pruning within the space of linear velocity and front wheel steering angle to select the optimal instruction. This invention solves the technical problems of discontinuous paths, dynamic instability, and poor obstacle avoidance safety in multi-task operations of self-balancing bicycle robots, effectively and significantly improving the safety, smoothness, and efficiency of robot operations in complex unstructured environments.

The application discloses a kind of intelligent vehicle local path planning method, device and storage medium, wherein method includes: according to positioning information and high-precision map information, the reference driving path required for intelligent car local path planning is obtained;According to the planning starting point of current planning frame is solved according to tracking effect;Smooth the reference driving path, obtain path frenet coordinate system according to the reference driving path after smoothing;Static obstacles and oncoming vehicles are projected to path frenet coordinate system, SL graph is generated, and path planning trajectory is obtained according to SL graph;Dynamic obstacle short-time prediction trajectory is projected to speed frenet coordinate system, ST graph is generated, and speed planning trajectory is obtained according to ST graph;Path planning trajectory and speed planning trajectory are coupled on natural coordinate system, and restore into high-dimensional local planning trajectory.The application uses SL graph and ST graph to process path and speed respectively, improves efficiency, and can be widely applied to trajectory planning technical field in unmanned driving.

This application provides a method and system for generating obstacle avoidance trajectories based on a diffusion strategy, relating to the field of intelligent control technology. The method acquires the operating status information, task target information, and environmental status information of a mobile robot; determines the local planning area requiring local obstacle avoidance planning; identifies obstacle occupancy information within the local planning area; determines the location and local deformation of facility boundaries within the local planning area; and determines the effective passage boundary. Starting from multiple initial noise sequences, it performs multi-step inverse diffusion denoising iterations under the constraints of guiding condition features to generate multiple candidate obstacle avoidance trajectories. Candidate obstacle avoidance trajectories that conflict with obstacle occupancy information, exceed the effective passage boundary, or do not meet execution constraints are eliminated, and the target obstacle avoidance trajectory is determined from the remaining candidate trajectories. This method can improve the safety and passage efficiency of local obstacle avoidance trajectories in operating environments where the boundaries of facilities on both sides of the passage may deform.

The present application relates to village planning space information processing technical field, disclose a kind of village planning real scene three-dimensional data acquisition method, device, equipment and storage medium, by establishing village rough three-dimensional scene and dividing planning observation unit, make data evaluation process by overall coverage determination turn to local planning expression determination, introduce planning interaction record and respectively calculate initial collection completeness, planning importance and required collection completeness, so that system can identify lane facade, courtyard edge, eaves lower interface and public space boundary and other local space area that influence planning expression effect, by calculating reinforcement requirement value and generating supplementary collection record table, so that supplementary collection process is transformed into differentiating reinforcement processing for key planning observation unit, finally by integrating initial oblique image and supplementary collection image, realize local depth estimation and real scene three-dimensional fusion, improve the three-dimensional expression quality of key area such as narrow lane, courtyard boundary and low-texture facade.

The application provides a spatiotemporal tensor task priority local planning method for unmanned surface vehicle, and belongs to the technical field of autonomous unmanned system navigation and control, and comprises the following steps: constructing a unified three-dimensional spatiotemporal tensor based on environment perception data; the three-dimensional spatiotemporal tensor integrally encodes static obstacle information and future prediction occupation information of dynamic obstacles, supports constant time complexity collision feasibility query of any position and time combination; generating guidance reference information containing expected heading based on time parameterized reference trajectory; generating a candidate control action set based on the current motion state, performing collision constraint verification on the candidate control action based on the three-dimensional spatiotemporal tensor, screening to obtain a safe action set satisfying the non-collision constraint, and selecting an optimal control action in the safe action set with the only optimization target of minimizing the deviation between the predicted ship heading and the expected heading; and step four, generating a local planning path based on the optimal control action, and controlling the unmanned surface vehicle to sail.

The application provides a binding robot system and a path planning method and a working method thereof, the path planning method comprising: global planning: performing rapid and low-dimensional rough planning in a task space, establishing a safe buffer zone around an obstacle by introducing a concept of an extended distance; adopting a bidirectional search strategy to improve search efficiency; and generating a safe and smooth 'path main line' through a smoothing optimization strategy; local planning: performing real-time local planning under the guidance of the global 'path main line' by using a neural network algorithm based on a QR-DQN architecture to obtain an optimal binding path; and the neural network algorithm is trained by integrating target guidance and obstacle avoidance as heuristic knowledge into a reward function. Compared with the prior art, the binding robot system and the path planning method and the working method thereof provided by the application can significantly improve the adaptability, efficiency and reliability of robot binding.